Estimating the effect of circulating vitamin D on body mass index: a Mendelian randomization study

BackgroundNumerous observational studies have shown an association between higher circulating 25 hydroxyvitamin D (vitamin D) and lower body mass index (BMI). Whether this represents a causal effect remains unclear. Mendelian randomization (MR) is an approach to causal inference that uses genetic variants as instrumental variables to estimate the effect of exposures on outcomes of interest. MR estimates are not biased by confounding, reverse causation and other biases in the same way as conventional observational estimates. In this study, we used MR with new data on genetic variants associated with vitamin D to estimate the effect of vitamin D on BMI. MethodsWe selected single nucleotide polymorphisms (SNPs) which were associated with vitamin D in a recent large genome-wide association study (GWAS) at genome-wide significance as instruments for vitamin D. We used inverse variance weighted models and further assessed individual SNPs that showed evidence of an effect, and biologically informed SNPs located in genetic regions previously associated with vitamin D, for associations with other traits at genome-wide significance, using Wald ratio estimation. ResultOur main results showed no evidence of an effect of vitamin D on BMI (estimated standard deviation change in BMI per standard deviation change in vitamin D: -0.003, 95% confidence interval [-0.06, 0.06]). This was also supported by pleiotropy robust sensitivity analyses. Individual SNPs that showed evidence of an effect of vitamin D on either lower or higher BMI were strongly associated with numerous other traits suggesting high levels of horizontal pleiotropy. Biologically informed SNPs showed no evidence of a causal effect of vitamin D on BMI and showed substantially less evidence of pleiotropic effects. ConclusionThe observed association between vitamin D and BMI is unlikely to be due to a causal effect of vitamin D on BMI. We also show how additional evidence can be incorporated into an MR study to interrogate individual SNPs for potential pleiotropy and improve interpretation of results.